The evaluation and application of a fully disaggregate method for trip matrix estimation with platoon dispersion

This paper addresses the problem of estimating an Origin–Destination (O–D) matrix with platoon dispersion from fully disaggregate data: that is, the passage times of vehicles at the entries and exits or the origins and destinations of a network. Given a list of entry times and a list of exiting times, a fully disaggregate method or a matching method tries to match each pair of entry–exiting times such that the resultant journey times for each O–D pair fit the given distributions best. Bell et al. formulated the problem of finding the most likely set of matches as a 0–1 assignment problem. In this paper, two estimators will be considered: maximum likelihood estimator and the matching-Furness technique. It will be shown that the maximum likelihood estimation can be formulated more generally as a transportation problem. The matching-Furness method is investigated by use of simulated traffic data and is applied to a set of real data collected on the Brescia–Padova motorway network in Italy. The matching-Furness method gives consistently better estimates than the least squares estimator and the linked static-dynamic correlation model. The method is therefore suitable for off-line estimations for general networks.